week 9 self similarity
Here is my comparison for track 1 till 7 and 10 with a structure analysis of the playlist in which only John Cage is credited on Spotify.
- Is the original, you can see that it exist out of 3 parts. Track 3 is the closest (if you follow the big lines) in form to track 1. The other tracks are just all over the place and some of them could be a total different piece.
Week 9 sceptrogram
You can see very clear in map1 that there is a magnitude of 0 around c01. c02 has the highest magnitude overall.
Map track 2, 6, 10 and 4 in order of most to least have a similar magnitude aroung c02. It is noticable tht there is a magnitude around c03 in track 3 and 7. Track 5 could again be another piece.
Introduction
Dear Reader,
For this project, I want to analyse different versions of the musical piece: 4’33’’ by John Cage. 4’33’’ is a piece made by John Cage. It is not my favourite song, but it questions perfectly what music is and what it can be. I am interested in which information I can get about the different versions, by analysing it with Rstudios. That is why I made 4 playlists with different versions of 4’33’‘. The first playlist contains all the 57 versions I could find on Spotify, some of them are just parts of the pieces. The 2nd playlist are all the version made and played/performed by John Cage. The 3rd playlist are the versions that do not give credits to John Cage, but has the same or a similar name. The 4th playlist consist of interpretation of 4’33’’.
The lists that I use are these list: Playlist 1: https://open.spotify.com/playlist/34a7macvtzIMePk2fRq4oC?si=78984ccde61a4f44 Playlist 2: https://open.spotify.com/playlist/5sWJTo3Zxy9oTf5CCqc624?si=2db9da0f122a49ae Playlist 3: https://open.spotify.com/playlist/7qwMKRYgTiRLOLszqDYyj9?si=76be1e131ac94e7d Playlist 4:https://open.spotify.com/playlist/383bBCxqKWd8tpvWrU9yYH?si=ae28a61a0874436b
These are the libraries that I use: library(tidyverse) library(spotifyr) library(compmus)
I hope that I have informed you well enough and enjoy reading my analysis of 4’33”’s.
Kind regards, Lucius Groot
week 8
Week 8 part2
I do not know what I can conclude from the map tracks; but apparently every 4’33’’ has its own key; while I cannot hear a key if I am listening.
week 7
In week 7, I experiment with different codes. You can see what my results are in the following tabs:
Summary of the lists
# A tibble: 1 × 12
mean_speechiness mean_acousticness mean_liveness sd_speechiness
<dbl> <dbl> <dbl> <dbl>
1 NA NA NA NA
# ℹ 8 more variables: sd_acousticness <dbl>, sd_liveness <dbl>,
# median_speechiness <dbl>, median_acousticness <dbl>, median_liveness <dbl>,
# mad_speechiness <dbl>, mad_acousticness <dbl>, mad_liveness <dbl># A tibble: 1 × 12
mean_speechiness mean_acousticness mean_liveness sd_speechiness
<dbl> <dbl> <dbl> <dbl>
1 0.180 0.234 0.316 0.180
# ℹ 8 more variables: sd_acousticness <dbl>, sd_liveness <dbl>,
# median_speechiness <dbl>, median_acousticness <dbl>, median_liveness <dbl>,
# mad_speechiness <dbl>, mad_acousticness <dbl>, mad_liveness <dbl># A tibble: 1 × 12
mean_speechiness mean_acousticness mean_liveness sd_speechiness
<dbl> <dbl> <dbl> <dbl>
1 0.0417 0.445 0.204 0.0279
# ℹ 8 more variables: sd_acousticness <dbl>, sd_liveness <dbl>,
# median_speechiness <dbl>, median_acousticness <dbl>, median_liveness <dbl>,
# mad_speechiness <dbl>, mad_acousticness <dbl>, mad_liveness <dbl># A tibble: 1 × 12
mean_speechiness mean_acousticness mean_liveness sd_speechiness
<dbl> <dbl> <dbl> <dbl>
1 NA NA NA NA
# ℹ 8 more variables: sd_acousticness <dbl>, sd_liveness <dbl>,
# median_speechiness <dbl>, median_acousticness <dbl>, median_liveness <dbl>,
# mad_speechiness <dbl>, mad_acousticness <dbl>, mad_liveness <dbl># A tibble: 1 × 12
mean_speechiness mean_acousticness mean_liveness sd_speechiness
<dbl> <dbl> <dbl> <dbl>
1 NA NA NA NA
# ℹ 8 more variables: sd_acousticness <dbl>, sd_liveness <dbl>,
# median_speechiness <dbl>, median_acousticness <dbl>, median_liveness <dbl>,
# mad_speechiness <dbl>, mad_acousticness <dbl>, mad_liveness <dbl># A tibble: 1 × 12
mean_speechiness mean_acousticness mean_liveness sd_speechiness
<dbl> <dbl> <dbl> <dbl>
1 NA NA NA NA
# ℹ 8 more variables: sd_acousticness <dbl>, sd_liveness <dbl>,
# median_speechiness <dbl>, median_acousticness <dbl>, median_liveness <dbl>,
# mad_speechiness <dbl>, mad_acousticness <dbl>, mad_liveness <dbl>The summary I let Rstudio made of my lists: It is possible to make a summary of 4’33’’, but not if there are too many songs in one playlist.
Valence/Energy/Mode
I want to know of both the lists: Valence versus energy + the mode
I will have to reconsider the setting of the plots.
Valence/Energy/Mode in a smoothcurve
I want to know of both the lists: How can there be a key? What makes that there are different energies and how can some be negative?
The code of the homework week 7
***
I took some inspiration of the homework for my longest code ever
Histogram of the lists
The histogram I made about both the lists:
nothing special